Monitoring of deforestation and land use in Indonesia with multitemporal ERS data

Kuntz, Steffen; Siegert, Florian

doi:10.1080/014311699211822

Cited by 39 publications

(23 citation statements)

References 6 publications

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“…A third factor is the effect of climatic events on tropical forests, such as the 1997-1998 El Nino, which caused extreme drought and increased wild fires in tropical regions (Kuntz andSiegert 1999, Siegert et al 2001). Since selectively logged forests were more susceptible to fire (Holdsworth and Uhl 1997), this climate anomaly could have increased the degradation in logged forests through drought and fire, thereby enhancing the detection of selectively logged forests due to their more heavily degraded canopies.…”

Section: Final Considerationsmentioning

confidence: 98%

“…Satellite-based remote sensing, focusing on forest and non-forest analyses, has been used for many years for land use and cover change assessment in different tropical forest regions in the world (Fearnside et al 1990, Skole and Tucker 1993, Kuntz and Siegert 1999. Data from these studies, such as the rate of tropical deforestation, are often used to estimate human effects on the global carbon cycle (Fearnside 1997, Houghton 1997, Page et al 2002.…”

Section: Introductionmentioning

confidence: 98%

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Multi‐temporal assessment of selective logging in the Brazilian Amazon using Landsat data

Matricardi

Skole

Cochrane

et al. 2007

International Journal of Remote Sensing

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Large-scale selective logging is a relatively new activity in the Amazon and its full consequences have yet to be evaluated. Impacts by selective logging alone have been estimated to increase approximately 4-7% of the annual carbon release from deforestation. In this research, visual interpretation and semi-automated remote sensing techniques were applied to identify and map areas of selective logging in tropical terra firme (upland) forests together with the correlated multiannual measurement results for 1992, 1996, and 1999, for the Brazilian Amazon. The research results indicate that selective logging is rapidly increasing in both intensity (regional) and area (basin-wide). By 1992, at least 5980 km 2 of forest had been logged. During the 1992During the -1996During the and 1996During the -1999 periods the area impacted expanded by an additional 10 064 km 2 , and 26 085 km 2 , respectively. Selective logging within protected areas increased more than twofold between 1992 and 1996, and more than fivefold between 1996 and 1999 in that region. We also estimated that at least 3689 km 2 had been actively logged in 1992, an additional 5107 km 2 , and 11 638 km 2 , had been logged in 1996 and 1999, and at least 10% of total logged forests detected in 1999 were previously logged in the period of analysis.

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Section: Final Considerationsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 98%

Multi‐temporal assessment of selective logging in the Brazilian Amazon using Landsat data

Matricardi

Skole

Cochrane

et al. 2007

International Journal of Remote Sensing

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“…Kuntz and Siegert (1999) suggested the use of ERS-1 SAR CVV band to monitor forest conversion and land cover in tropical forest environments but with additional information derived from texture and multitemporal ERS-1 SAR data.…”

Section: Sar Bands Selected By Discriminant Analysismentioning

confidence: 99%

Classifying regenerating forest stages in Amazônia using remotely sensed images and a neural network

Kuplich

2006

Forest Ecology and Management

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“…These studies have been using C-band data (ERS, Radarsat) and have been carried out in boreal regions, in North America [8,32,47,57] and in Siberia [77], in the Mediterranean region [34,35], and in tropical regions [62,90]. Burnt scar mapping has been found possible, which has generally been explained by changes in soil humidity [47].…”

Section: Radarmentioning

confidence: 99%

The contribution of remote sensing to the assessment of drought effects in forest ecosystems

Deshayes

Guyon²,

Jeanjean

et al. 2006

Ann. For. Sci.

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-Due to their synoptic and monitoring capacities, Earth observation satellites could prove useful for the assessment and evaluation of drought effects in forest ecosystems. The objectives of this article are: to briefly review the existing sources of remote sensing data and their potential to detect drought damage; to review the remote sensing applications and studies carried out during the last two decades aiming at detecting and quantifying disturbances caused by various stress factors, and especially those causing effects similar to drought; to explore the possibility to use some of the different available systems for setting up a strategy more adapted to monitoring of drought effects in forests.drought / forest / remote sensing / satellite Résumé -Contribution de la télédétection à l'évaluation des effets de la sécheresse sur les écosystèmes forestiers. Grâce à leurs capacités de surveillance continue, les satellites d'observation de la Terre pourraient s'avérer utiles pour l'évaluation des effets de la sécheresse sur les écosystèmes forestiers. Les objectifs de cet article sont : de passer en revue rapidement les sources actuelles de données de télédétection et leur potentiel pour la détection des dommages dus à la sécheresse ; de passer en revue les études et applications de télédétection conduites pendant les deux dernières décennies et visant à détecter et quantifier les perturbations induites par différents facteurs de stress, et en particulier ceux causant des effets semblables à ceux de la sécheresse ; d'explorer la possibilité d'utiliser certains des systèmes disponibles pour définir une stratégie adaptée au suivi continu des effets de la sécheresse sur les forêts.sécheresse / forêt / télédétection / satellite

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Monitoring of deforestation and land use in Indonesia with multitemporal ERS data

Cited by 39 publications

References 6 publications

Multi‐temporal assessment of selective logging in the Brazilian Amazon using Landsat data

Multi‐temporal assessment of selective logging in the Brazilian Amazon using Landsat data

Classifying regenerating forest stages in Amazônia using remotely sensed images and a neural network

The contribution of remote sensing to the assessment of drought effects in forest ecosystems

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